Regression-Type Estimation of the Parameters of Stable Laws
提出一种回归型方法估计稳定分布的四个参数，估计量一致且近似无偏，计算量小，效率优于多数现有方法，并应用于四家公司的股票价格数据。
Abstract A regression-type method of estimating the four parameters of a stable distribution is presented. The estimators found are consistent and approximately unbiased for moderately large sample sizes. Their efficiencies, found through a simulation study, are greater than those of most other estimators for large portions of the parameter space. Moreover, the amount of computation involved is minimal and apparently less than that needed by the methods of Paulson, Holcomb, and Leitch (1975) and of maximum likelihood (DuMouchel 1971). Finally, this method is applied to stock price data from four corporations.